The present invention relates to an image data processing method and an image data processing system which can be adopted or employed in image data compression processing and the like.
In the high-efficiency coding technique of the image for which the use of communication media and/or recording media is prerequisite, the technique based on discrete cosine transform (DCT) is extensively adopted. However, one of the intrinsic problems inherent to the compression procedure using the DCT can be seen in that when the compression ratio is increased, then block distortions, mosquito noise and the like will become visually perceived, imposing thus limitation on the realizable compression ratio.
Under the circumstances, the novel compression procedures have been developed and proposed in recent years in an attempt for enhancing the compression ratio. Among others, the data compression technique adopting a so-called wavelet transformation, one of the subband encoding techniques, attracts attention. Parenthetically, this technique will hereinafter be referred to as the wavelet. As the wavelet lacks the concept of xe2x80x9cblockxe2x80x9d, there is no inter-block distortion generated in the DCT, so that the image quality is visually improved to an appreciable extent.
For having better understanding of the present invention, a conventional wavelet compression/expansion method known heretofore will be described in some detail.
FIG. 7 is a block diagram showing generally and schematically a system configuration of a conventional wavelet image compression system. In the figure, reference numeral 1001 denotes an original image. Reference numerals 1002, 1003 and 1004 denote subband decomposition units for layer-0, layer-1 and layer-2 provided at stages #0, #1 and #2, respectively. Reference numeral 1005 denotes an insignificant-space-estimation deletion unit.
FIG. 11 is a block diagram which shows representatively a structure of the subband decomposition unit shown in FIG. 7. In FIG. 11, reference numeral 1401 denotes a horizontal low-pass filter, 1402 denotes a horizontal high-pass filter, 14031 and 14032 denote horizontal down-samplers, 14041, and 14042 denote vertical low-pass filters, 14051 and 14052 denote vertical high-pass filters, and reference numerals 14061-14064 denote vertical down-samplers.
For carrying out the wavelet transformation, the horizontal low-pass filter 1401 receives two-dimensional input data 1455 shown in FIG. 11 to perform the low-frequency filtering operation in the horizontal direction. Thereby, horizontal low-frequency data 1456 is generated. The horizontal high-pass filter 1402 receives the two-dimensional input data 1455 to perform the high-frequency filtering operation in the horizontal direction. Thereby, horizontal high-frequency data 1457 is generated. These data 1456 and 1457 then undergo the horizontal down-sampling operation by the horizontal down-samplers 14031 and 14032, respectively. Thereby, horizontal DC separate data 1458 and horizontal H separate data 1459 are generated.
The horizontal DC separate data 1458 then undergoes the filtering operation in the vertical direction by the vertical low-pass filter 14041, and the vertical high-pass filter 14051 to generate horizontal DC vertical low-frequency data 1460 and horizontal DC vertical high-frequency data 1461, respectively. Similarly, the horizontal H separate data 1459 undergoes the filtering operation in the vertical direction by the vertical low-pass filter 14042 and the vertical high-pass filter 14052 to generate horizontal H vertical low-frequency data 1462 and horizontal H vertical high-frequency data 1463, respectively. These data 1460-1463 then undergo the vertical down-sampling operation by the vertical down-samplers 14061-14064 to generate DC separate data 1451, LH separate data 1452, HL separate data 1453 and HH separate data 1454, respectively. In this way, the wavelet transformation can be realized. The subband decomposition processing at the succeeding stage is performed substantially in the same manner.
FIG. 9 is a block diagram showing generally and schematically a system configuration of a conventional wavelet image expansion system. In FIG. 9, reference numeral 1101 denotes an insignificant-space-estimation development unit, 1102 denotes a layer-0 subband synthesis unit, 1103 denotes a layer-1 subband synthesis unit, and 1104 denotes a layer-2 subband synthesis unit. Reference numeral 1105 denotes an expanded image.
FIG. 8 is a block diagram showing generally and schematically an arrangement of the conventional insignificant-space-estimation deletion unit 1005 shown in FIG. 7. In FIG. 8, reference numeral 1201 denotes a layer-1 HL insignificant space estimation module for estimating an HL insignificant space of the layer-1 on the basis of the layer-2 HL space. Reference numeral 1202 denotes a layer-1 LH insignificant space estimation module for estimating an LH insignificant space of the layer-1 on the basis of the layer-2 LH space. Reference numeral 1203 denotes a layer-1 HH insignificant space estimation module for estimating an HH insignificant space of the layer-1 on the basis of the layer-2 HH space. Reference numerals 1204, 1205 and 1206 denote a layer-1 HL insignificant space deletion module, a layer-1 LH insignificant space deletion module, a layer-1 HH insignificant space deletion module, respectively, for deleting the relevant insignificant spaces in the layer-1. Reference numerals 1207, 1208 and 1209 denote layer-0 HL, LH and HH insignificant space estimation modules for estimating relevant insignificant spaces in the layer-0 from the HL, LH and HH insignificant spaces of the layer-1, respectively. Reference numerals 1210, 1211 and 1212 denote HL, LH and HH insignificant space deletion modules for deleting the HL, LH and HH insignificant spaces of the layer-0, respectively.
FIG. 10 is a block diagram showing a structure of the conventional insignificant-space-estimation development unit 1101 shown in FIG. 9. In FIG. 10, reference numeral 1301 denotes a layer-1 HL development module, 1302 denotes a layer-1 LH development module, 1303 denotes a layer-1 HH development module, 1304 denotes a layer-0 HL development module, 1305 denotes a layer-0 LH development module, and 1306 denotes a layer-0 HH development module.
FIG. 12 is a block diagram showing a structure of the subband synthesis unit (see FIG. 9). In FIG. 12, reference numerals 15011-15014 denote vertical up-samplers, 15021, and 15022 denote vertical low-pass filters, 15031, and 15032 denote vertical high-pass filters, 15041 and 15042 denote horizontal up-samplers, 1505 denotes a horizontal low-pass filter, and 1506 denotes a horizontal high-pass filter.
Next, description will be directed to the operation of the conventional wavelet compression/expansion system. When the original image 1001 is supplied, the layer-0 subband decomposition unit 1002 shown in FIG. 7 receives the original image data 1061 to perform the first wavelet transformation. Thereby, wavelet data (i.e., layer-0 DC data 1062, layer-0 HL data 1063, layer-0 LH data 1064 and layer-0 HH data 1065) are generated. These wavelet data will hereinafter be referred to as layer-0 wavelet data.
The layer-1 subband decomposition unit 1003 receives the layer-0 wavelet DC data 1062 to perform the second wavelet transformation. Thereby, wavelet data (i.e., layer-1 DC data 1066, layer-1 HL data 1067, layer-1 LH data 1068 and layer-1 HH data 1069) are generated. These wavelet data will hereinafter be referred to as layer-1 wavelet data.
Then, the layer-2 subband decomposition unit 1004 receives the layer-1 DC wavelet data 1066 to perform the third wavelet transformation. Thereby, wavelet data (i.e., layer-2 DC data 1051, layer-2 HL data 1052, layer-2 LH data 1053, and layer-2 HH data 1054) are generated. These wavelet data will hereinafter be referred to as layer-2 wavelet data.
In order that the data compression is performed on the basis of the correlation in the frequency direction among the wavelet data generated in the manners mentioned above, the insignificant-space-estimation deletion unit 1005 receives the wavelet data 1052-1054, 1067-1069, and 1063-1065 which contain no DC component. Then, the insignificant-space-estimation deletion unit 1005 performs the data compression by deleting the insignificant spaces.
FIG. 13 is a view for illustrating the wavelet space. In the figure, reference numerals 1601, 1602 and 1603 denote HH, LH and HL wavelet spaces of the layer-0, respectively. Reference numerals 1604, 1605 and 1606 denote HH, LH and HL wavelet spaces of the layer-1, respectively. Reference numerals 1607, 1608 and 1609 denote HH, LH and HL wavelet spaces of the layer-2, respectively. Reference numeral 1610 denotes a layer-2 DC wavelet space.
It is to be mentioned that the wavelet data exhibits the correlation between the adjacent layers. For example, when a value held by a given area 1652 in the space 1606 that is the wavelet data of the layer-1 is small, then the value held by an analogous area 1651 in the space 1603 that is the wavelet data of layer-0 having the same component can be regarded to be small with a high probability. Further, when the value of the given area 1652 is sufficiently small, the analogous area 1651 in the space 1603 may be defined as having a minimum value. In that case, the data of the analogous area 1651 is unnecessary for the decoding so far as the data of the given area 1652 is available. Accordingly, when the value of the given area 1652 is detected to be smaller than a given threshold value in the coding processing, the analogous area 1651 in the adjacent layer can be decided to be an insignificant space to be deleted from the space 1603. As a result, it can contribute to the improvement of the data compression efficiency. Upon the decoding, the value of the given area 1652 is checked. When it is found that the value of the given area 1652 is not greater than the threshold value referenced at the time of coding, the wavelet space can be reconstituted by embedding the minimum value in the space 1603.
Now, description will be made in concrete of the processing for deleting the insignificant space as executed by the insignificant-space-estimation deletion unit 1005. In FIG. 8, the layer-1 HL insignificant space estimation module 1201 receives the layer-2 HL wavelet data 1052 to perform the threshold value decision. Thereby, the minimum-value-area estimation of the layer-1 HL data 1067 that is the data of the layer lower by one rank than the data 1052 is performed to generate the layer-1 HL insignificant space estimation data 1251. Similarly, the other insignificant space estimation modules 1202 and 1203 receive the relevant wavelet data of the layer-2 (i.e., the layer-2 LH data 1053 and the layer-2 HH data 1054) to perform the minimum-value-area estimation in the data of the one-rank lower layer (i.e., layer-1). Thereby, the layer-1 LH insignificant space estimation data 1252 and the layer-1 HH insignificant space estimation data 1253 are generated.
The layer-1 HL insignificant space deletion module 1204 receives the layer-1 HL insignificant space estimation data 1251 and the layer-1 HL data 1067 to delete the data in the insignificance-estimated area. Thereby, the layer-1 HL compressed data 1055 is generated. In a similar manner, the layer-1 LH insignificant space deletion module 1205 generates the layer-1 LH compressed data 1056 on the basis of the layer-1 LH insignificant space estimation data 1252 and the layer-1 LH data 1068. Further, the layer-1 HH insignificant space deletion module 1206 generates the layer-1 HH compressed data 1057 on the basis of the layer-1 HH insignificant space estimation data 1253 and the layer-1 HH data 1069.
Similarly, the layer-0 insignificant space estimation modules 1207, 1208 and 1209 receive the layer-1 compressed data 1055, 1056 and 1057 to perform the minimum-value-area estimation of the data in the one-rank lower layer (i.e., the layer-0), respectively. Thereby, the layer-0 insignificant space estimation data 1254, 1255 and 1256 are generated. Then, the layer-0 compressed data are generated on the basis of the layer-0 insignificant space estimation data 1254, 1255 and 1256.
Next, description will turn to the operation of the conventional decoder implemented in the form of the wavelet image expansion unit. In FIG. 9, the layer-0 subband synthesis unit 1102 receives the compressed wavelet data of the layer-2 (i.e., the layer-2 DC data 1051, the layer-2 HL data 1052, the layer-2 LH data 1053 and the layer-2 HH data 1054) to perform the reverse wavelet transformation. Thereby, the layer-1 DC expanded data 1158 is generated.
In this conjunction, the reverse wavelet transformation can be realized by means of the vertical p-sampler 15011, shown in FIG. 12 that receives the DC input data 1552 to perform the up-sampling operation in the vertical direction. Thereby, the DC up-sampled data 1556 is generated. Likewise, the vertical up-samplers 15012-15014 receive the HL input data 1553, the LH input data 1554 and the HH input data 1555 to generate the up-sampled data 1557, 1558 and 1559, respectively.
Subsequently, the vertical low-pass filter 15021 and the vertical high-pass filter 15031 receive the DC up-sampled data 1556 and the HL up-sampled data 1557, respectively, to perform the filtering reverse mapping transformation in the vertical direction. Thereby, the horizontal DC synthesized data 1560 is generated. Likewise, the vertical low-pass filter 15022 and the vertical high-pass filter 15032 receive the LH up-sampled data 1558 and the HH up-sampled data 1559, respectively, to generate the horizontal H synthesized data 1561.
The horizontal up-sampler 15041 receives the horizontal DC synthesized data 1560 to perform the up-sampling operation in the horizontal direction. Thereby, the horizontal DC up-sampled data 1562 is generated. Similarly, the horizontal up-sampler 15042 receives the horizontal H synthesized data 1561 to generate the horizontal H up-sampled data 1563. The horizontal low-pass filter 1505 and the horizontal high-pass filter 1506 receive the horizontal DC up-sampled data 1562 and the horizontal H up-sampled data 1563, respectively, to perform the filtering reverse mapping transformation in the horizontal direction. Thereby, the synthesized data 1551 is generated.
In FIG. 9, the insignificant-space-estimation development unit 1101 receives the data 1052-1060 of the individual layers to decode the data compressed by deleting the insignificant spaces. Thereby, the expanded data 1152-1157 of the individual layers are generated.
Now, concrete description will be made of the decoding of the data compressed by deleting the insignificant spaces. FIG. 10 is a block diagram showing concretely the structure of the insignificant-space-estimation development unit 1101. In FIG. 10, the insignificant space estimation module 1201 receives the layer-2 HL data 1052 to estimate the minimum value area in the data of the one-rank lower layer (i.e., the layer-1 HL compressed data 1055). Thereby, the HL insignificant space development/estimation data 1351 is generated. Similarly, the insignificant space estimation modules 1202 and 1203 receive the component data of the layer-2 (i.e., the layer-2 LH data 1053 and the layer-2 HH data 1054) to estimate the minimum value areas in the data of the respective one-rank lower layer. Thereby, the layer-1 LH insignificant space development/estimation data 1352 and the layer-1 HH insignificant space development/estimation data 1353 are generarted.
The layer-1 HL development module 1301 receives the layer-1 HL insignificant space development/estimation data 1351 and the layer-1 HL compressed data 1055 to embed the minimum value in the insignificance-estimated area. Thereby, the HL expanded data 1152 is generated. Similarly, the layer-1 LH development module 1302 generates the LH expanded data 1153 by embedding the minimum value in the insignificance-estimated area on the basis of the layer-1 LH compressed data 1056 and the layer-1 LH insignificant space development/estimation data 1352. The layer-1 HH development module 1303 generates the HH expanded data 1154 by embedding the minimum value in the insignificance-estimated area on the basis of the layer-1 HH compressed data 1057 and the layer-1 HH insignificant space development/estimation data 1353.
Then, the layer-0 HL insignificant space estimation module 1207 receives the layer-1 HL expanded data 1152 to perform the threshold value decision for estimating the minimum value area in the data of the one-rank lower layer (i.e., the layer-0 HL compressed data 1058). Thereby, the layer-0 HL insignificant space development/estimation data 1354 is generated. Similarly, the layer-0 LH insignificant space estimation module 1208 receives the component data of the layer-1 (i.e., the layer-1 LH expanded data 1153) to estimate the minimum value area in the data of the one-rank lower layer. Thereby, the layer-0 LH insignificant space development/estimation data 1355 is generated. The layer-0 HH insignificant space estimation module 1209 receives the component data of the layer-1 (i.e., the layer-1 HH expanded data 1154) to estimate the minimum value area in the data of the one-rank lower layer. Thereby, the layer-0 HH insignificant space development/estimation data 1356 is generated.
Finally, the layer-0 HL development module 1304 receives the layer-0 HL insignificant space development/estimation data 1354 and the layer-0 HL compressed data 1058 to embed the minimum value in the insignificance-estimated area. Thereby, the layer-0 HL expanded data 1155 is generated. Similarly, the layer-0 LH development module 1305 generates the layer-0 LH expanded data 1156 by embedding the minimum value to the insignificance-estimated area on the basis of the layer-0 LH compressed data 1059 and the layer-0 LH insignificant space development/estimation data 1355. The layer-0 HH development module 1306 generates the layer-0 HH expanded data 1157 by embedding the minimum value to the insignificance-estimated area on the basis of the layer-0 HH compressed data 1060 and the layer-0 HH insignificant space development/estimation data 1356. In this way, the decoding of the wavelet data is carried out.
In FIG. 9, reference numeral 1158 designates layer-1 DC expanded data, and 1159 designates layer-0 DC expanded data. Reference numeral 1151 designates the expanded image data. The layer-1 subband synthesis unit 1103 receives the wavelet data 1158, 1152, 1153 and 1154 of the layer-1 to generate the layer-0 DC expanded data 1159. Further, the layer-2 subband synthesis unit 1104 receives the wavelet data 1159, 1155, 1156 and 1157 of the layer-0 to generate the expanded image data 1151. Through the procedure described above, the image data can be expanded.
However, the conventional image data processing system suffers shortcomings that the accuracy in predicting or estimating the insignificant area is relatively low, incurring degradation in the image compression efficiency. More specifically, for a signal having only high frequency components, there may arise such situation that the high-frequency components are estimated as the insignificant spaces because of unavailability of the correlation between the low-frequency components and the high-frequency components. Thus, there are some cases where the degradation with regard to the resolution of the image is occurred.
It is an object of the present invention to provide an image data processing method and an image data processing system which can ensure the enhanced accuracy for the estimation of the insignificant space as well as the improvement for the image data compression efficiency.
In order to achieve the object, the present invention allows the insignificant space estimation of the high-frequency components with high accuracy and reliability by deleting an insignificant space from data with high accuracy in the following manner. Upon the prediction of a space in which significant data of high-frequency data after the subband division is exists, in the case that any significant data exists in the space estimated as an insignificant space, a significance attribute indicating the presence of insignificant data in the insignificance-decided space corresponding to the space in which it exists. Then, the insignificant space to be compressed is re-estimated on the basis of a threshold value of the insignificance-decided space added the significance attribute and the significance attribute.
The first aspect of the present invention is a coding or encoding apparatus for an image data processing system, which comprises: means for performing wavelet transformation; means for estimating and deleting an insignificant space to be subjected to code-deletion on the basis of a threshold decision for the insignificant space and significance attribute indicating presence of significant data; means for detecting the presence of the significant data in the space estimated as the insignificant space by the estimated means; and means for adding the significance attribute to the insignificance-decided space corresponding to the space in which the significant data exists. According to the first aspect, the accuracy of the prediction on the basis of the frequency correlation upon the coding can be enhanced. Thereby, the image quality degradation due to the compression can be prevented without increasing the amount of codes upon the coding.
The second aspect of the present invention is a decoding apparatus for an image data processing system, which comprises: means for estimating an insignificant space to be subjected to code-deletion on the basis of a threshold comparison decision of an insignificance-decided space and a significance attribute indicating presence of significant data; means for embedding an insignificant data in the space decided to be insignificant by the estimating means and for developing data generated by the coding method mentioned previously in the areas other than the insignificant space; and means for performing a reverse wavelet transformation. According to the second aspect, the accuracy of the prediction on the basis of the frequency correlation upon the decoding can be enhanced. Thereby, the image quality degradation of the expanded image can be prevented without increasing the amount of codes upon the coding.
The above and other objects, features and attendant advantages of the present invention will more easily be understood by reading the following description of the preferred embodiments thereof taken, only by way of example, in conjunction with the accompanying drawings.